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Doctoral Research Study

What I Studied

Since artificial intelligence has become the technology of choice to solve complex business problems, the purpose of this qualitative multiple-case study was to explore voluntary AI governance motivations, the actions taken by for-profit enterprise leaders, and the resulting organizational outcomes.

Abstract Background

Investigated 46 Modern Situations
(All episodes recorded from March 2021 - April 2022)

I identified 172 possible case studies and vetted those to net 46 individual cases plus one cross-case study. The final dataset included cases from financial services, retail, healthcare, software, agriculture (sustainability), manufacturing, construction, and many examples that cross industries.

Abstract Surface

How My Study is Valuable

Lessons learned created best practices findings and conclusions for business leaders, government leaders, and politicians to inform the wise creation of standards, policies, regulations, and laws. These lessons also inform AI/ML product developers, GTM positioning, and buyers’ journey selling.

Abstract Blue Light


Stay tuned! I'm digging through the data right now.

Neon Lights



Degree Conferred July 2023

Black Diamond

Data Methods

My study employed two separate data gathering methods.

  1. Given the proliferation of podcasts recently recorded and made publicly available, I carefully curated a set of podcast interviews of business leaders and consultants responsible for applying AI to yield business benefits. In a nod to the need for poetry in life, I used AI technology for data identification, gathering, and processing.

  2. As a committed advocate of diversity within all areas of AI, I wanted to expand insights past my own perspective. To that end, I gathered input from a varied group of reviewers.

  • Based upon a written synthesis of each case study provided in a survey format, each reviewer shared their perspective on motivations, actions, and outcomes.

  • The dedication of these individuals is deeply appreciated as 18 technology-savvy professionals provided partial dataset responses and 11 completed a full review of all 47 cases. Reviewers shared as much as 6 hours of their personal time to provide these valuable insights. Together, they contributed more than 60 hours of diverse perspective.

Illuminated Abstract Shapes


Stay tuned!

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